Metadata from IPBES on Zenodo

Technical Guideline Series

Abstract

To be added

GitHub Repository

Methods

Setup and get records from Zenodo

#|

# Load the zen4R library
library(zen4R)
library(openalexR)

Thank you for using openalexR!
To acknowledge our work, please cite the package by calling `citation("openalexR")`.
To suppress this message, add `openalexR.message = suppressed` to your .Renviron file.

library(dplyr)

Attaching package: 'dplyr'

The following objects are masked from 'package:stats':

    filter, lag

The following objects are masked from 'package:base':

    intersect, setdiff, setequal, union

fn <- file.path("data", "ipbes_zenodo_records")
if (!file.exists(paste0(fn, ".rds"))) {
  # Authenticate with Zenodo
  zen <- ZenodoManager$new(token = Sys.getenv("Zenodo_IPBES_RO"))

  # Get the community ID
  community_id <- "ipbes"

  # Get the community info
  community <- zen$getCommunityById(community_id)

  # Get all deposits with ipbes somwhere
  ipbes_zenodo <- zen$getRecords(community_id)

  # Filter records based on the community ID
  ipbes <- sapply(
    ipbes_zenodo,
    function(record) {
      "ipbes" %in% unlist(record$metadata$communities)
    }
  )

  ipbes_zenodo <- ipbes_zenodo[ipbes]

  rm(ipbes)

  saveRDS(ipbes_zenodo, paste0(fn, ".rds"))
} else {
  ipbes_zenodo <- readRDS(paste0(fn, ".rds"))
}

Get the dois and titles of the records

dois <- data.frame()

for (i in seq(length.out = length(ipbes_zenodo))) {
  record <- ipbes_zenodo[[i]]
  dois <- rbind(
    dois,
    c(
      doi = record$metadata$doi,
      year = record$metadata$publication_date,
      title = record$metadata$title
    )
  )
}

names(dois) <- c("doi", "year", "title")

dois <- tibble::as_tibble(dois)

#|
fn <- file.path(".", "data", "ipbes_works.rds")
if (!file.exists(fn)) {
  # Define the maximum chunk size
  chunk_size <- 50
  # Split the vector into chunks
  doi_chunks <- split(
    dois$doi,
    ceiling(seq_along(dois$doi) / chunk_size)
  )

  ipbes_works <- lapply(
    doi_chunks,
    function(dois) {
      openalexR::oa_query(doi = dois) |>
        openalexR::oa_request(count_only = FALSE)
    }
  ) |>
    unlist(recursive = FALSE)

  saveRDS(ipbes_works, file = fn)
} else {
  ipbes_works <- readRDS(file = fn)
}

Results

Keywords

Number of keywords per Deposit

ipbes_zenodo |>
  sapply(
    FUN = function(x) {
      x$metadata$keywords |>
        unlist() |>
        length()
    }
  ) |>
  table() |>
  knitr::kable(
    col.names = c("Number of keywords", "n")
  )

Number of keywords	n
0	129
1	61
2	44
3	77
4	21
5	10
6	13
7	8
8	1
9	1
10	1

Keywords used in the deposits

ipbes_zenodo |>
  sapply(
    FUN = function(x) {
      x$metadata$keywords |>
        unlist()
    }
  ) |>
  unlist() |>
  table() |>
  sort(decreasing = TRUE) |>
  knitr::kable(col.names = c("Keyword", "n"))

Keyword	n
IPBES	178
Data management report	47
Assessment	36
data management policy	31
Values Assessment	30
Invasive alien species	27
Global Assessment	20
Supplementary material	19
Europe and Central Asia Assessment	18
Chapter 4	15
Summary for Policymakers	14
Table	13
Chapter 2	12
Figure	11
SPM	11
Full assessment report	9
Values	9
Chapter	8
Chapter 3	8
Chapter 6	7
Chapter 5	6
Regional assessment	6
Africa Assessment	5
Decision	4
Summary for policymakers	4
Biodiversity	3
Chapter 1	3
data and knowledge management policy	3
data management	3
Future	3
ILK	3
Land Degradation and Restoration Assessment	3
Pollination Assessment	3
Scenarios and Models Assessment	3
Valuation	3
Americas Assessment	2
Arabic	2
Asia and the Pacific Assessment	2
Capacities	2
Chinese	2
Data Management	2
Decision-making	2
Diverse	2
FAIR	2
French	2
Just	2
Methods	2
Operationalization	2
Russian	2
Spanish	2
stakeholder engagement	2
survey	2
Sustainable	2
active data management	1
Anthrome	1
Approaches	1
Archetypes	1
Biocultural conservation	1
Biome	1
Brightspot cases	1
CARE	1
CARE principles	1
Climate change	1
Climate Change	1
Conceptualization	1
Constitutions	1
COVID-19	1
Data and knowledge management policy	1
data backup	1
Data Management Policy	1
Data Management Report, Nature Futures Framework	1
Data Policy	1
Dataset	1
Decision making	1
Diverse values	1
DOI	1
Earth Stewardship	1
FAIR principles	1
Gap	1
global, species rarity, endemicity	1
Indicators	1
Indigenous Peoples and local communities	1
IPBES, Data Management Policy	1
IPBES, Senckenberg, Data Management, Policy, FAIR	1
IPBES, Values, Assessment, Figures, Chapter 1	1
IPBES, Values, SPM, Values	1
IPCC	1
IPCCC	1
Knowledge Management	1
long-term vision	1
Methodological	1
Methodological guidance	1
Methodologies	1
Model	1
Nature	1
Nature Futures Framework	1
open science	1
Option	1
Pandemics	1
Pathway	1
Plural Value Approach	1
Policy	1
Policy initiatives	1
Policy instruments	1
Pollination assessment	1
Scenario	1
scenarios, biodiversity, ecosystem services, nature’s contributions to people, nature futures, IPBES, visioning, narratives	1
Science-Policy	1
Stakeholder Survey	1
Transformative change	1
Transformative governance	1
VA	1
Values assessment	1
Zenodo	1

Licenses and Access

Licenses

#|

ipbes_zenodo |>
  sapply(
    FUN = function(x) {
      l <- x$metadata$license
      if (is.null(l)) {
        l <- "NULL"
      }
      return(l)
    }
  ) |>
  unlist() |>
  table(useNA = "always") |>
  knitr::kable(
    col.names = c(
      "license",
      "n"
    )
  )

license	n
cc-by-4.0	346
NULL	20
NA	0

Access Rights

#|

ipbes_zenodo |>
  sapply(
    FUN = function(x) {
      x$metadata$access_right
    }
  ) |>
  table(useNA = "always") |>
  knitr::kable(
    col.names = c(
      "access right",
      "n"
    )
  )

access right	n
embargoed	2
open	320
restricted	44
NA	0

The non-open deposits are:

ipbes_zenodo |>
  sapply(
    FUN = function(x) {
      if (x$metadata$access_right != "open") {
        result <- list(
          title = substr(x$title, 1, 40),
          access_right = x$metadata$access_right,
          link = paste0("<a href='", x$links$self_html, "' target='_blank'>", x$doi, "</a>")
        )
      } else {
        result <- NULL
      }
    }
  ) |>
  dplyr::bind_rows() |>
  dplyr::arrange(title) |>
  knitr::kable()

title	access_right	link
2020 Stakeholder Survey of the Intergove	restricted	10.5281/zenodo.4121916
DISCARD_IPBES Invasive Alien Species Ass	restricted	10.5281/zenodo.10052573
Hotspots of endemism and rarity - Figure	restricted	10.5281/zenodo.4957887
IPBES Core Indicators - Harmonized Datas	restricted	10.5281/zenodo.4564763
IPBES Country Borders Package	restricted	10.5281/zenodo.5883633
IPBES IAS assessment, data management re	restricted	10.5281/zenodo.5746076
IPBES Invasive Alien Species Assessment,	embargoed	10.5281/zenodo.5766070
IPBES Invasive Alien Species Assessment,	embargoed	10.5281/zenodo.5706617
IPBES Long-term Vision on Data and Knowl	restricted	10.5281/zenodo.5513474
IPBES TCA Chapter 1. Analysis of contrib	restricted	10.5281/zenodo.12532308
IPBES TCA Chapter 1. Analysis of knowled	restricted	10.5281/zenodo.11657378
IPBES TCA Chapter 1. Creation of a case	restricted	10.5281/zenodo.10260234
IPBES TCA Chapter 1. Literature and data	restricted	10.5281/zenodo.10245400
IPBES TCA Chapter 1. Literature review d	restricted	10.5281/zenodo.11657640
IPBES TCA Chapter 1. Literature review o	restricted	10.5281/zenodo.10246745
IPBES TCA Chapter 2. Content analysis of	restricted	10.5281/zenodo.10548648
IPBES TCA Chapter 2. Systematic literatu	restricted	10.5281/zenodo.10252320
IPBES TCA Chapter 3. Identification of o	restricted	10.5281/zenodo.10250564
IPBES TCA Chapter 3. Review of knowledge	restricted	10.5281/zenodo.10250534
IPBES TCA Chapter 3. Systematic review o	restricted	10.5281/zenodo.10523261
IPBES TCA Chapter 4. Review of literatur	restricted	10.5281/zenodo.10252305
IPBES TCA Chapter 4. Review of literatur	restricted	10.5281/zenodo.10250610
IPBES TCA Chapter 4. Review of literatur	restricted	10.5281/zenodo.10251409
IPBES TCA Chapter 4. Review of literatur	restricted	10.5281/zenodo.10252251
IPBES TCA Chapter 4. Review of literatur	restricted	10.5281/zenodo.10251326
IPBES TCA Chapter 5. Shifting power tow	restricted	10.5281/zenodo.10304954
IPBES TCA Chapter 5. Addressing unsustai	restricted	10.5281/zenodo.10262310
IPBES TCA Chapter 5. Biodiversity conser	restricted	10.5281/zenodo.10261652
IPBES TCA Chapter 5. Capacity building a	restricted	10.5281/zenodo.10262495
IPBES TCA Chapter 5. Inventory options f	restricted	10.5281/zenodo.10264136
IPBES TCA Chapter 5. Review of options f	restricted	10.5281/zenodo.10262647
IPBES TCA Chapter 5. Views and Values /	restricted	10.5281/zenodo.10305489
IPBES TCA. Corpus of literature on trans	restricted	10.5281/zenodo.10479548
IPBES nexus assessment - Chapter 2, dat	restricted	10.5281/zenodo.10119408
IPBES nexus assessment - Chapter 2, dat	restricted	10.5281/zenodo.10119473
IPBES nexus assessment - Chapter 2, dat	restricted	10.5281/zenodo.10119431
IPBES nexus assessment - Chapter 2, dat	restricted	10.5281/zenodo.10119511
IPBES nexus assessment - Chapter 3, dat	restricted	10.5281/zenodo.10119540
IPBES nexus assessment - Chapter 4, dat	restricted	10.5281/zenodo.10119750
IPBES nexus assessment - Chapter 4, dat	restricted	10.5281/zenodo.10119625
IPBES nexus assessment - Chapter 5.1 –	restricted	10.5281/zenodo.10119872
IPBES nexus assessment - Chapter 5.2 –	restricted	10.5281/zenodo.10119960
IPBES nexus assessment - Chapter 5.4 –	restricted	10.5281/zenodo.10119986
IPBES nexus assessment - Chapter 6, dat	restricted	10.5281/zenodo.10120033
IPBES nexus assessment - Chapter 2, data	restricted	10.5281/zenodo.10101030
Interactive Dashboard of the 2020 Stakeh	restricted	10.5281/zenodo.5046948

IPBES Deposits Network

fn <- file.path("data", "ipbes_network.rds")

if (!file.exists(fn)) {
  relations <- lapply(
    ipbes_zenodo,
    function(rec) {
      relation <- rec$metadata$related_identifiers
      if (is.null(relation)) {
        return(NULL)
      }
      result <- rec$metadata$related_identifiers |>
        dplyr::bind_rows() |>
        dplyr::mutate(
          year = rec$metadata$publication_date,
          doi = rec$metadata$doi,
          title = rec$metadata$title,
          keywords = rec$metadata$keywords |>
            unlist() |>
            paste(collapse = "; "),
        )
      return(result)
    }
  ) |>
    dplyr::bind_rows() |>
    dplyr::left_join(
      y = read.table("inst/relation_direction.txt", header = TRUE),
      by = "relation"
    )

  nodes <- unique(
    c(
      relations$doi,
      relations$identifier
    )
  )

  edges <- rbind(
    relations |>
      filter(
        direction == "to"
      ) |>
      dplyr::select(
        from = doi,
        to = identifier
      ),
    relations |>
      filter(
        direction == "from"
      ) |>
      dplyr::select(
        from = doi,
        to = identifier
      )
  )

  network <- list(
    nodes = nodes,
    edges = edges
  )

  ipbes_network <- list(
    nodes = nodes,
    edges = edges,
    relations = relations
  )
  rm(nodes, edges, relations)

  saveRDS(ipbes_network, fn)
} else {
  ipbes_network <- readRDS(fn)
}

fn <- file.path("figures", "ipbes_network.html")

## Simple forceNetwork
networkData <- data.frame(
  src = ipbes_network$edges$from,
  target = ipbes_network$edges$to,
  stringsAsFactors = FALSE
)

nodes <- data.frame(
  name = ipbes_network$nodes,
  # title = ipbes_network$nodes$,
  # doi = ipbes_network$nodes$doi,
  stringsAsFactors = FALSE
)

nodes$id <- 0:(nrow(nodes) - 1)

# create a data frame of the edges that uses id 0:9 instead of their names
edges <- networkData |>
  left_join(nodes, by = c("src" = "name")) |>
  select(-src) |>
  rename(source = id) |>
  left_join(nodes, by = c("target" = "name")) |>
  select(-target) |>
  rename(target = id) |>
  mutate(width = 1)

# # make a grouping variable that will match to colours
nodes$group <- 1

# nodes$oa_id <- nodes$name
# nodes$name <- nodes$author

# control colours with a JS ordinal scale
# ColourScale <- 'd3.scaleOrdinal()
#                         .domain(["key_paper", "other"])
#                      .range(["#FF6900", "#694489"]);'

openDOI <- "window.open(d.doi)"

nwg <- networkD3::forceNetwork(
  Links = edges,
  Nodes = nodes,
  Source = "source",
  Target = "target",
  NodeID = "name",
  # Nodesize = "nodesize",
  Group = "group",
  # Value = "width",
  opacity = 0.9,
  zoom = TRUE,
  # colourScale = DT::JS(ColourScale),
  fontSize = 20,
  legend = TRUE,
  clickAction = openDOI
)

nwg$x$nodes$doi <- nodes$doi

networkD3::saveNetwork(
  nwg,
  file = fn,
  selfcontained = TRUE
)

unlink(
  gsub(
    fn,
    pattern = "\\.html",
    replacement = "_files"
  ),
  recursive = TRUE,
  force = TRUE
)


nwg

IPBES Deposits Network

ipbes_network$relations |>
  dplyr::select(
    year,
    doi,
    relation,
    identifier,
    direction,
    title,
    keywords
  ) |>
  IPBES.R::table_dt(
    fixedColumns = list(leftColumns = 6)
  )

IPBES deposits on Zenodo with OpenAlex ids

This is a quick and dirty table - it could made nicer - but it fulfills it’s purpose.

ipbes_works |>
  openalexR::works2df() |>
  dplyr::select(
    # year = publication_year,
    # title,
    doi,
    oa_id = id
  ) |>
  dplyr::mutate(
    doi = gsub(pattern = "https://doi.org/", replacement = "", x = doi)
  ) |>
  dplyr::left_join(
    x = dois,
    by = c("doi" = "doi")
  ) |>
  dplyr::mutate(
    doi = paste0("<a href='https://doi.org/", doi, "' target='_blank'>", doi, "</a>"),
    oa_id = ifelse(
      is.na(oa_id),
      "",
      paste0("<a href='", oa_id, "' target='_blank'>", gsub(pattern = "https://openalex.org/", replacement = "", oa_id), "</a>")
    )
  ) |>
  select(
    doi,
    oa_id,
    year,
    title
  ) |>
  IPBES.R::table_dt()